Noise characteristics of ocean-bottom seismometer data in the Bransfield Strait, Antarctica

• Main Authors: Schmidt-Aursch, Mechita C., Almendros, Javier, Geissler, Wolfram, Wilcock, William
• Format: Conference Object
• Language: unknown
• Published: 2022
• Subjects: Antarc*; Antarctica; Bransfield Strait; Sea ice
• Online Access: https://epic.awi.de/id/eprint/57417/

All seismological data contain not only desired source signals, but also noise. There are various natural and artificial noise sources like wind, waves, traffic, industry, etc. Data recorded by ocean-bottom seismometers (OBS) show a different content of noise than onshore data; mainly because the OBS are located directly in one of the major noise generators: the oceans. Oceanic microseisms dominate the recordings over a broad frequency band, and there are several noise sources not known onshore, e.g. marine mammals, ship traffic, marine seismic surveys and especially in the polar regions sea ice and icebergs. In the framework of the BRAVOSEIS project, eight broadband ocean-bottom seismometers were deployed for one year in the Bransfield Strait, Antarctica. The ambient noise was helpful to correct the clock drift of the data loggers by means of noise cross-correlations. High-resolution probabilistic power spectral densities and spectrograms were calculated for all stations and channels to study the noise-generating processes. An analysis of tidal signals were performed for various time series including temperature recordings. Although all OBS were located within the same basin, they differ significantly in their noise characteristics. The noise spectrum was divided into several frequency bands. Some bands show seasonal variations, others are persistent during the entire year. A few noise signatures are coherent between all OBS, this is typical for origins far away. Most noise sources occur very locally and are specific for each OBS depending on parameters like water depth or the abundance of deep water currents. Generally, the noise properties are complex and show a great variation in time and space.